Embodiments of the invention relate generally to the monitoring of a condition of an electromechanical machine. Specifically, embodiments of the invention relate to a method and system for monitoring the condition of a drive-train system and bearing of an electromechanical machine based on current signal analysis (CSA).
Conventionally, the monitoring of mechanical abnormalities in electromechanical systems has been mainly performed using vibration signals. It has been observed that mechanical faults in the drive-train produce vibrations in radial rotor movement which in turn produce torque oscillations at the rotor mechanical rotating frequency. The monitoring and study of the rotor mechanical rotating frequency may lead to detecting mechanical faults associated with the drive-train system. However, condition monitoring using vibration signals has numerous disadvantages such as signal background noise due to external excitation motion, sensitivity to the installation position, and their invasive measurement nature.
Other condition monitoring techniques are based on the observation that the load torque oscillations cause the stator current to be phase modulated, whereby the stator current signature is analyzed for detecting mechanical perturbations due to fault. Such current monitoring techniques are receiving more and more attention in the detection of mechanical faults in electric machines since it offers significant economic savings and easy implementation. For example, in the case of bearing fault detection in electromechanical machines, bearing failures may be categorized into single-point defects or generalized roughness faults. The single-point defects have been detected by using motor current signal analysis (MCSA) with bearing mechanical characteristic frequencies and by considering these types of anomalies as eccentricity fault. However, for generalized roughness faults the characteristic bearing fault frequencies are not observable or may not exist, particularly at an early stage. In addition, irrespective of the type of fault, the bearing fault signatures are usually subtle compared to the dominant components in the sampled stator current such as the supply fundamental harmonics, eccentricity harmonics, and slot harmonics. Unlike bearing vibration monitoring, for which industry standards have been developed from long-time field experience, the field experience in stator current monitoring is limited, and significant difficulties exist. For example, the magnitude of bearing fault signatures may vary at different applications given that the bearing fault signatures in the stator current are already subtle. Further, gearbox monitoring using stator current signal analysis has been rarely proposed although gearboxes are widely used in industrial applications.
Therefore, there exists a need for an improved method and system for monitoring the condition of a drive-train system, specifically a gearbox and bearing, using current signature analysis.